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Optimising neural networks for identification of wood defects using the bees algorithm

Pham, Duc Truong, Soroka, Anthony John, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh and Packianather, Michael Sylvester 2006. Optimising neural networks for identification of wood defects using the bees algorithm. Presented at: 2006 IEEE International Conference on Industrial Informatics, Singapore, 16-18 August 2006. Proceedings of the 2006 IEEE International Conference on Industrial Informatics, Singapore, 16-18 August 2006. IEEE, pp. 1346-1351. 10.1109/INDIN.2006.275855

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Abstract

This paper presents an application of the bees algorithm (BA) to the optimisation of neural networks for wood defect detection. This novel population-based search algorithm mimics the natural foraging behaviour of swarms of bees. In its basic version, the algorithm performs a kind of neighbourhood search combined with random search. Following a brief description of the algorithm, the paper gives the results obtained for the wood defect identification problem demonstrating the efficiency and robustness of the new algorithm.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Uncontrolled Keywords: Ant colony optimization; Bonding; Genetic algorithms; neural networks; Particle swarm optimization; Polynomials; Pulp manufacturing; Robustness; Search methods; Semiconductor optical amplifiers
Publisher: IEEE
ISBN: 0780397002
Related URLs:
Last Modified: 10 Oct 2017 14:43
URI: http://orca-mwe.cf.ac.uk/id/eprint/37633

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